A Bibliometric Survey of Fashion Analysis using Artificial Intelligence

In the 21st century, clothing fashion has become an inevitable part of every individual human as it is considered a way to express their personality to the outside world. Currently the traditional fashion business models are experiencing a paradigm shift from being an experience-based business strategy implementation to a data driven intelligent business improvisation. Artificial Intelligence is acting as a catalyst to achieve the infusion of data intelligence into the fashion industry which aims at fostering all the business brackets such as supply chain management, trend analysis, fashion recommendation, sales forecasting, digitized shopping experience etc. The field of “Fashion AI\u27\u27 is still under research progress because the fashion data is a multifaceted entity which is available in any of the forms like an image, video, text and numerical values. Therefore, it becomes a challenging research arena. There is a paucity of a common study which can provide a bird’s eye view about the research efforts and directions. In this paper, the authors represent a bibliometric survey of the AI based fashion analysis domain based on the Scopus database. The study was conducted by retrieving 581 Scopus research papers published from 1975-2020 and analysed to find out critical insights such as publication volume, co-authorship networks, citation analysis, and demographic research distribution. The study revealed that significant contribution is made via concept propositions in conferences and some papers published in the journal. However, there is a scope of lots of research work in the direction of improving fashion industry with AI techniques

A Bibliometric Survey of Fashion Analysis using Artificial Intelligence

In the 21st century, clothing fashion has become an inevitable part of every individual human as it is considered a way to express their personality to the outside world. Currently the traditional fashion business models are experiencing a paradigm shift from being an experience-based business strategy implementation to a data driven intelligent business improvisation. Artificial Intelligence is acting as a catalyst to achieve the infusion of data intelligence into the fashion industry which aims at fostering all the business brackets such as supply chain management, trend analysis, fashion recommendation, sales forecasting, digitized shopping experience etc. The field of “Fashion AI\u27\u27 is still under research progress because the fashion data is a multifaceted entity which is available in any of the forms like an image, video, text and numerical values. Therefore, it becomes a challenging research arena. There is a paucity of a common study which can provide a bird’s eye view about the research efforts and directions. In this paper, the authors represent a bibliometric survey of the AI based fashion analysis domain based on the Scopus database. The study was conducted by retrieving 581 Scopus research papers published from 1975-2020 and analysed to find out critical insights such as publication volume, co-authorship networks, citation analysis, and demographic research distribution. The study revealed that significant contribution is made via concept propositions in conferences and some papers published in the journal. However, there is a scope of lots of research work in the direction of improving fashion industry with AI techniques

SGDiff: A Style Guided Diffusion Model for Fashion Synthesis

This paper reports on the development of \textbf{a novel style guided diffusion model (SGDiff)} which overcomes certain weaknesses inherent in existing models for image synthesis. The proposed SGDiff combines image modality with a pretrained text-to-image diffusion model to facilitate creative fashion image synthesis. It addresses the limitations of text-to-image diffusion models by incorporating supplementary style guidance, substantially reducing training costs, and overcoming the difficulties of controlling synthesized styles with text-only inputs. This paper also introduces a new dataset -- SG-Fashion, specifically designed for fashion image synthesis applications, offering high-resolution images and an extensive range of garment categories. By means of comprehensive ablation study, we examine the application of classifier-free guidance to a variety of conditions and validate the effectiveness of the proposed model for generating fashion images of the desired categories, product attributes, and styles. The contributions of this paper include a novel classifier-free guidance method for multi-modal feature fusion, a comprehensive dataset for fashion image synthesis application, a thorough investigation on conditioned text-to-image synthesis, and valuable insights for future research in the text-to-image synthesis domain. The code and dataset are available at: \url{https://github.com/taited/SGDiff}.Comment: Accepted by ACM MM'2

FIRST: A Million-Entry Dataset for Text-Driven Fashion Synthesis and Design

Text-driven fashion synthesis and design is an extremely valuable part of artificial intelligence generative content(AIGC), which has the potential to propel a tremendous revolution in the traditional fashion industry. To advance the research on text-driven fashion synthesis and design, we introduce a new dataset comprising a million high-resolution fashion images with rich structured textual(FIRST) descriptions. In the FIRST, there is a wide range of attire categories and each image-paired textual description is organized at multiple hierarchical levels. Experiments on prevalent generative models trained over FISRT show the necessity of FIRST. We invite the community to further develop more intelligent fashion synthesis and design systems that make fashion design more creative and imaginative based on our dataset. The dataset will be released soon.Comment: 11 pages, 8 figure

Transforming shape: a simultaneous approach to the body, cloth and print for garment and textile design (synthesising CAD with manual methods)

Printed textile and garment design are generally taught and practised as separate disciplines. Integrated CAD software enables textile and clothing designers to envisage printed garments by assimilating graphic imagery with 2D garment shapes, and 3D visualisations. Digital printing can be enlisted to transpose print-filled garment shapes directly onto cloth. This research challenges existing 2D practice by synthesising manual and CAD technologies, to explore the integration of print design and garment shape from a simultaneous, 3D perspective. This research has identified three fundamental archetypes of printed garment styles from Twentieth Century fashion: 'sculptural', 'architectural' and 'crossover'. The contrasting spatial characteristics and surface patterning inherent in these models provided tlýe theoretical and practical framework for the research. Design approaches such as'textile-led', 'garment-led'and 'the garment as canvas' highlighted the originality of the simultaneous design method, which embraces all of these concepts. This research recognises the body form as a positive influence within the printed textile and printed garment designing process, whereby modelled fabric shapes can be enlisted to determine mark making. The aim of the practice, to create printed garment designs from a 3D perspective, was facilitated by an original method of image capture, resulting in blueprinted toiles, or cyanoforms, that formed the basis of engineer-printed garments and textiles. Integrated CAD software provided the interface between manual modelling, design development and realisation, where draping software was employed to digitally craft 3D textiles. The practical and aesthetic characteristics of digital printing were tested through the printing of photographic-style, integrated garment prototypes. The design outcomes demonstrate that a simultaneous approach to the body, cloth and print can result in innovative textile vocabulary, that'plays a proactive role within the design equation, through its aesthetic integration with garment and form. The integration of print directly with the garment contour can result in a 3D orientated approach to printed garment design that is empathetic with the natural body shape

Transforming shape: hybrid practice as group activity

Printed textile and garment design are generally taught and practised as separate disciplines. Integrated CAD software enables textile and clothing designers to envisage printed garments by assimilating graphic imagery with 2D garment shapes and 3D visualizations. Digital fabric printing can be employed to transpose print-filled garment shapes directly onto cloth. During a recently completed practice-led PhD (1998-2003), I researched the aesthetic design potential of combining new CAD technology with garment modelling methods to create new innovative printed textiles/garments. The merging of physical and screen-based making resulted in a hybrid 3D approach to the body, cloth and print referred to as the 'simultaneous design method'. In 2001 this hybrid practice provided the catalyst for a collaborative textile research project at the Nottingham Trent University, UK. The group included surface, shape and multimedia designers. The key group aim was to explore the transforming effects of computer-aided textile design through dialogues between two and three dimensions. In parallel with my own practice, print and embroidery were considered from a 3D starting-point through the relating of geometric cloth shapes to the form. Each designer took an idiosyncratic approach to the selection and integration of imagery with the shapes. The novel consideration of the final modelled textile at the start of the designing process influenced each designer in different ways, leading to a collection of contrasting, original outcomes that were displayed in the exhibition Transforming Shape (UK 2001, Denmark 2003). The exhibition demonstrated the design opportunities (and limitations) of new and existing technologies, specifically the relationship between innovative textile imagery and three-dimensional form. The designs illustrated the premise that surface designs can be engineered through different pattern shapes and that engineer-printed shapes transform the body